Understanding human language, like a human. And other tales of cognitive computing

Human cognition is incredibly flexible, partly because common-sense knowledge is uncertain but highly structured. Probabilistic programming languages (PPLs) provide a formal tool encompassing probabilistic uncertainty and compositional structure. I will show that PPLs allow us to model human language understanding as social reasoning grounded in structured common-sense knowledge. This framework captures vague adjectives (“Bob is tall’’), generic language (“boys are tall’’), hyperbole (“Bob is a hundred feet tall’’), and metaphor (“Bob is a giraffe’’). I will close with some implications this work has for the future of cognitive computing.